PURPOSE: French-American-British (FAB) classification of acute leukemia with genetic heterogeneity is important for treatment and prognosis. However, the distinct protein profiles that contribute to the subtypes and facilitate molecular definition of acute leukemia classification are still unclear. EXPERIMENTAL DESIGN: The proteins of leukemic cells from 61 cases of acute leukemia characterized by FAB classification were separated by two-dimensional electrophoresis, and the differentially expressed protein spots were identified by both matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) and tandem electrospray ionization MS (ESI-MS/MS). RESULTS: The distinct protein profiles of acute leukemia FAB types or subtypes were successfully explored, including acute myeloid leukemia (AML), its subtypes (M2, M3, and M5) and acute lymphoid leukemia (ALL), which were homogeneous within substantial samples of the respective subgroups but clearly differed from all other subgroups. We found a group of proteins that were highly expressed in M2 and M3, rather than other subtypes. Among them, myeloid-related proteins 8 and 14 were first reported to mark AML differentiation and to differentiate AML from ALL. Heat shock 27 kDa protein 1 and other proteins that are highly expressed in ALL may play important roles in clinically distinguishing AML from ALL. Another set of proteins up-regulated was restricted to granulocytic lineage leukemia. High-level expression of NM23-H1 was found in all but the M3a subtype, with favorable prognosis. CONCLUSIONS: These data have implications in delineating the pathways of aberrant gene expression underlying the pathogenesis of acute leukemia and could facilitate molecular definition of FAB classification. The extension of the present analysis to currently less well-defined acute leukemias will identify additional subgroups.
PURPOSE: French-American-British (FAB) classification of acute leukemia with genetic heterogeneity is important for treatment and prognosis. However, the distinct protein profiles that contribute to the subtypes and facilitate molecular definition of acute leukemia classification are still unclear. EXPERIMENTAL DESIGN: The proteins of leukemic cells from 61 cases of acute leukemia characterized by FAB classification were separated by two-dimensional electrophoresis, and the differentially expressed protein spots were identified by both matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) and tandem electrospray ionization MS (ESI-MS/MS). RESULTS: The distinct protein profiles of acute leukemia FAB types or subtypes were successfully explored, including acute myeloid leukemia (AML), its subtypes (M2, M3, and M5) and acute lymphoid leukemia (ALL), which were homogeneous within substantial samples of the respective subgroups but clearly differed from all other subgroups. We found a group of proteins that were highly expressed in M2 and M3, rather than other subtypes. Among them, myeloid-related proteins 8 and 14 were first reported to mark AML differentiation and to differentiate AML from ALL. Heat shock 27 kDa protein 1 and other proteins that are highly expressed in ALL may play important roles in clinically distinguishing AML from ALL. Another set of proteins up-regulated was restricted to granulocytic lineage leukemia. High-level expression of NM23-H1 was found in all but the M3a subtype, with favorable prognosis. CONCLUSIONS: These data have implications in delineating the pathways of aberrant gene expression underlying the pathogenesis of acute leukemia and could facilitate molecular definition of FAB classification. The extension of the present analysis to currently less well-defined acute leukemias will identify additional subgroups.
Authors: L Angenendt; S Reuter; D Kentrup; A S Benk; F Neumann; J Hüve; A C Martens; C Schwöppe; T Kessler; L H Schmidt; T Sauer; C Brand; J-H Mikesch; G Lenz; R M Mesters; C Müller-Tidow; W Hartmann; E Wardelmann; D Neri; W E Berdel; C Roesli; C Schliemann Journal: Leukemia Date: 2017-06-30 Impact factor: 11.528